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Microsoft ML Mastery: Empowering Data Scientists with Cutting-Edge Machine Learning Techniques
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Build and train machine learning models using Azure Machine Learning
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Prepare and process data for use in machine learning pipelines
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Deploy models to production environments with online and batch endpoints
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Monitor and retrain models using MLOps best practices
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Use AutoML to accelerate model development and evaluation
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Apply responsible AI principles to ensure ethical model deployment.
Overview
Off the shelf (OTS)
This course is designed for data scientists, software developers, AI engineers, data analysts, and business intelligence professionals who want to develop and deploy machine learning solutions using Microsoft technologies. It focuses on leveraging Azure Machine Learning to build and manage the end-to-end machine learning lifecycle in real-world scenarios.
A basic understanding of programming and data analysis concepts is recommended.
The Microsoft Machine Learning Training Course provides a hands-on introduction to the tools and techniques used to create, train, deploy, and monitor machine learning models within the Microsoft ecosystem. Participants will work with Azure Machine Learning to build scalable solutions, automate workflows using ML pipelines, and apply responsible AI practices. The course includes real-world case studies and practical labs to ensure participants can confidently implement machine learning projects from start to finish.
Key Topics Covered:
• Overview of machine learning concepts and Azure ML Studio
• Data preparation, ingestion, and feature engineering
• Training, tuning, and evaluating machine learning models
• Automated Machine Learning (AutoML) and ML pipelines
• Deployment to online and batch endpoints
• Monitoring and managing models using MLOps practices
• Applying responsible AI frameworks and model governance
• Industry case studies demonstrating ML applications
The course is delivered over two days and includes hands-on exercises to reinforce learning.
Delivery method
Virtual
Course duration
14 hours
Competency level
Working

Delivery method
-
Virtual
Course duration
14 hours
Competency level
-
Working
